Study on Intelligent Perception Internet of Things Apply in Mine Safety
| Autor: | Daoyuan Wang, Liangchen Xu, Jingzhao Li, Lin Sun |
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| Rok vydání: | 2020 |
| Předmět: |
History
Artificial neural network Computer science Process (engineering) media_common.quotation_subject Node (networking) Fault tolerance Kalman filter computer.software_genre Computer Science Applications Education Information extraction Human–computer interaction Perception Architecture computer media_common |
| Zdroj: | Journal of Physics: Conference Series. 1646:012146 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1646/1/012146 |
| Popis: | Due to the complexity, multi-source and heterogeneity of mine safety scene perception information, the mine safety monitoring system has some problems, such as slow perception, communication lag, lack of effective information extraction and intelligent decision-making, a mine safety situation perception self configuration system based on the Internet of things is proposed in this paper, the architecture and perception model of mine safety situation perception system are established, and the embedded neuron is designed mine safety monitoring system based on perceptual node and distributed neural network. The unscented Kalman filter is used to adjust the BP neural network to reconcile and process the multi-sensor parameter information. The simulation results show that the system has good fault tolerance and high precision of intelligent decision-making, which plays an important role in improving mine intelligent level and safety production. |
| Databáze: | OpenAIRE |
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